Gen AI- Lead/Manager

Job Title: Manager - Agentic Development Role and Responsibilities Lead the development of agentic systems that are more than just wrappers for LLM modelssystems that actively drive business outcomes with human-in-the-loop oversight Design and develop Multi-Agent Ecosystems where multiple specialized agents collaborate to solve complex problems using frameworks like LangGraph, or AutoGen Define "Agentic Thinking" and instill a mindset in the team where we build for Goals, not just Tasks. Lead the adoption of standardized protocols to connect AI assistants to our internal data and tools securely. Take ownership of full stack application development and oversee the end-to-end SDLC of AI-native applications. Incorporate human-in-the-loop design by developing UX/UI patterns wherein agents integrate seamlessly with outlined processes, operate autonomously up to a specified confidence threshold, and then gracefully hand off tasks for human approval Develop robust evaluation & Observability metrices to measure Agent Success Rate, Steps-to-Solution, and Cost-per-Task. Work closely with the business leads / designates to define workflows and be assertive enough to ensure we use the right tools for right outcomes instead of one size fits all kind of approach Mentor and develop a team of AI engineers who understand vector stores, RAG, and prompt orchestration. Essential skills required 7+ Years of Experience in software engineering, with at least 4-5 years focused on AI/ML and 1-2 years specifically in Generative AI/Agentic workflows. Hands-on expertise with LangGraph, CrewAI, AutoGen, or LlamaIndex for multi-step reasoning and orchestration. Deep understanding of RAG (Retrieval-Augmented Generation), context engineering, and long-term memory design for agents. Strong command of Python, vector databases (Pinecone, Weaviate, etc.), and cloud AI platforms (Azure AI Foundry) Experience with evaluation frameworks like LangSmith or Arize Phoenix to monitor agent performance, drift, and cost. Background in leading AI pods or CoEs for internal tools, with skills in Java, data engineering, and cross-functional collaboration. Ability to articulate technical solutions to stakeholders and drive innovation in agentic systems for SDLC optimization Exceptional communication and interpersonal skills, with the ability to collaborate effectively with diverse, cross-functional teams. Job Title: Manager - Agentic Development Role and Responsibilities Lead the development of agentic systems that are more than just wrappers for LLM modelssystems that actively drive business outcomes with human-in-the-loop oversight Design and develop Multi-Agent Ecosystems where multiple specialized agents collaborate to solve complex problems using frameworks like LangGraph, or AutoGen Define "Agentic Thinking" and instill a mindset in the team where we build for Goals, not just Tasks. Lead the adoption of standardized protocols to connect AI assistants to our internal data and tools securely. Take ownership of full stack application development and oversee the end-to-end SDLC of AI-native applications. Incorporate human-in-the-loop design by developing UX/UI patterns wherein agents integrate seamlessly with outlined processes, operate autonomously up to a specified confidence threshold, and then gracefully hand off tasks for human approval Develop robust evaluation & Observability metrices to measure Agent Success Rate, Steps-to-Solution, and Cost-per-Task. Work closely with the business leads / designates to define workflows and be assertive enough to ensure we use the right tools for right outcomes instead of one size fits all kind of approach Mentor and develop a team of AI engineers who understand vector stores, RAG, and prompt orchestration. Essential skills required 7+ Years of Experience in software engineering, with at least 4-5 years focused on AI/ML and 1-2 years specifically in Generative AI/Agentic workflows. Hands-on expertise with LangGraph, CrewAI, AutoGen, or LlamaIndex for multi-step reasoning and orchestration. Deep understanding of RAG (Retrieval-Augmented Generation), context engineering, and long-term memory design for agents. Strong command of Python, vector databases (Pinecone, Weaviate, etc.), and cloud AI platforms (Azure AI Foundry) Experience with evaluation frameworks like LangSmith or Arize Phoenix to monitor agent performance, drift, and cost. Background in leading AI pods or CoEs for internal tools, with skills in Java, data engineering, and cross-functional collaboration. Ability to articulate technical solutions to stakeholders and drive innovation in agentic systems for SDLC optimization Exceptional communication and interpersonal skills, with the ability to collaborate effectively with diverse, cross-functional teams.